Point target detection based on multiscale morphological filtering and an energy concentration criterion

The research on optical imaging characteristics of infrared dim point targets in the presence of nonstationary cloud clutter and random noise is necessary for target detection. We analyze the energy concentration of point targets that are less than 3×3 pixels in size and deduce a simulation model of the point target imaging process. Then we adopt omnidirectional multiscale structural elements to detect all the possible targets distributing in every direction. The adaptive threshold and the energy concentration criterion are employed to eliminate false alarms. Finally, the trajectory of point targets is obtained after the low-order recursive correlation. The results show that the detection probability of the proposed method reaches 99.8% with 0.2% false alarm probability. It demonstrates that the proposed method has a good performance to suppress complex background and random noise. Also, it has the advantage of low complexity and easy implementation in a real-time system.